Accuracy of enzyme-linked immunosorbent assays for quantification of antibodies against Aleutian mink disease virus
Bibliographic record
Abstract
There is a growing interest among mink ranchers to select their stock for tolerance to the Aleutian mink disease virus (AMDV). Enzyme-linked immunosorbent assays (ELISA) are used to identify mink which have low anti-AMDV antibody titres and are expected to tolerate the AMDV infection. The objective of this study was to calculate the accuracy of three ELISA systems which were performed on blood or serum of AMDV-inoculated American mink (Neovison vison) at five laboratories in Canada, USA, Finland, the Netherlands and Denmark. The accuracy was determined by comparing the ELISA results with antibody titres measured by the counter-immunoelectrophoresis (CIEP) using 10 two-fold serial dilutions of the plasma. Antibody titres of 880 black mink which were inoculated with a spleen homogenate from a naturally infected mink were measured between 16 and 176 weeks post-inoculation. Each ELISA result from every laboratory covered a wide range of antibody titres and the Spearman's rank correlation coefficients between CIEP and ELISA results from different laboratories varied between 0.41 and 0.83, indicating a low to moderate accuracy of ELISA systems for ranking mink by antibody titre. The recombinant VP2-based ELISA used in the Netherlands and Finland ranked the mink by antibody titres more accurately than did the AMDV-G-based ELISA platforms developed in Denmark and the USA, suggesting that the source of antigen was one of the factors affecting the accuracy of ELISA results. It was concluded that the ELISA systems, particularly those based on AMDV-G antigen, require further refinement to improve their accuracy for ranking mink by antibody titre.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".